A Beginner's Guide to the Mathematics of Neural Networks

By A.C.C. Coolen : https://lnkd.in/dsxSCBj

#ArtificialIntelligence #NeuralNetworks

✴️ @AI_Python_EN
🗣 @AI_Python_Arxiv
❇️ @AI_Python

Google AI has released TF-Ranking, a scalable TensorFlow-based library for learning-to-rank. It provides a unified framework to train, evaluate and serve a ranking model that includes a suite of state-of-the-art learning-to-rank algorithms, commonly used ranking metrics, easy visualization and also multi-item scoring for interference. Check out the article, paper and also the repo to walk through the tutorial examples. Myself can't wait to get started with this, in particular for my next search engine problem.
#deeplearning #machinelearning

Article: https://lnkd.in/e59qQdy
Paper: https://lnkd.in/ePwPVst
Github: https://lnkd.in/eZYE-UQ

✴️ @AI_Python_EN
🗣 @AI_Python_Arxiv
❇️ @AI_Python

PhD Program in "Information Systems for Data Science" at UMASS Boston

We are now accepting application for Fall 2019. Please share the application information with interested candidates. The contacts details are below.

More information can also be found on our website:
https://lnkd.in/eW9Aud6

Interested applicants can contact:
Ehsan Elahi
Associate Professor
Director of the PhD Program (IS for Data Science)
College of Management
University of Massachusetts, Boston
Email: ehsan.elahi@umb.edu
Phone: 617-287-7881

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

A visual introduction to machine learning, Part II

http://bit.ly/2N0T42K

#AI #DeepLearning #MachineLearning #DataScience

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Data science = Statistics +
Data preprocessing +
Machine learning +
Scientific inquiry +
Visualization +
Business Analytics +
Programming +
Empathy +
Communication + ...

—> To solve a real problem.

Data Science involves anything you do with data to solve real problems.

Be a problem solver.

And use data to help guide you to the solution.

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

François Chollet:

Pre-trained network for image super resolution (in Keras): https://github.com/idealo/image-super-resolution … An evening project would be to export it to TF.js to run in the browser on user-uploaded photos

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Learn probabilistic programming with TensorFlow Probability, from the ground up. The Bayesian Methods for Hackers book is now available in open source in TFP! Read post here ↓

Link Review


❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

30 Free Courses in #NeuralNetworks, #MachineLearning, #Algorithms, and #AI — https://bit.ly/2p7zQMB #abdsc #BigData #DataScience #DeepLearning #DataScientists

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

The Athlete and the Machine: New Trends in #AI and Sports Technology https://buff.ly/2MJzIiG #MachineLearning

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Exciting news from #NeurIPS – the European Laboratory for Learning and Intelligent Systems (ELLIS) has been announced! The centre will support research and help industry leverage #AI.

https://nvda.ws/2roKRfK

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

The Nytimes Data Science Group is searching for multiple full-time data scientists with a focus on machine learning. This is a great group of people working on interesting and important problems.

More info: https://nytimes.wd5.myworkdayjobs.com/en-US/DataInsights/job/New-York-NY/Data-Scientist--machine-learning-_REQ-004142

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

😁
❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Excited to present practical fairness paper "Why is My Classifier Discriminatory?" at #NeurIPS2018

papers.nips.cc/paper/7613-why-is-my-classifier-discriminatory

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

NeurIPS 2018 video talk collection #NeurIPS2018

https://buff.ly/2EaUFBC

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

👉 If you like our channel, i invite you to share it with your friends:
Our channel in english: ✴️ @AI_Python_EN
Our Daily arXiv Channel: 🗣 @AI_Python_Arxiv

BTW: Thank you for joining :)

Very comprehensive article on transfer learning. It covers the theory behind transfer learning in general and then how it can be used for deep learning. He then also presented two hands-on case studies where he used transfer learning in a CV classification task for first a binary class problem and then second multi-label classes. Code is also provided using Keras with the TensorFlow backend. Definitely check this article out. Transfer learning has a high practical importance for machine learning practitioners.
#deeplearning #machinelearning

Article: https://lnkd.in/daa6_UB
Github: https://lnkd.in/dhxXcRg

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Papers with Code: https://paperswithcode.com

#ArtificialIntelligence #DeepLearning #MachineLearning #NeuralNetworks #Technology


❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

PracticalAI: A practical approach to learning machine learning

By Goku Mohandas: https://lnkd.in/eyFbdCC

#machinelearning #naturallanguageprocessing #jupyter #python #pytorch


❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

Comixify: Transform video into a comics. They used a 2-stage approach: (a) frame selection and (b) style transfer. The results look pretty cool!

paper: https://lnkd.in/eszcexU
demo: https://lnkd.in/edrtfPd
test video: https://lnkd.in/ebWpPRD

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

The AI art gallery from NeurIPS Creativity workshop

AI Art Gallery: http://aiartonline.com

#NeurIPS2018

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

My 13-minute oral presentation at hashtag#NeurIPS2018 summarizing our world models paper. I felt like the weight of the world (model) was finally lifted off my shoulders after giving the talk.

article → https://lnkd.in/fa36JNH
paper → https://lnkd.in/gPjH_NJ


❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN